Empowered Patient Podcast Leveraging Vocal Biomarkers for Early Detection of Neurological Diseases with Henry O’Connell Canary Speech
Henry O'Connell is the CEO and Co-Founder of Canary Speech, which analyzes voice biomarkers to detect various medical conditions, including neurological disorders like Alzheimer's, Parkinson's, and cognitive decline. Their approach looks at the underlying mechanisms of speech controlled by the central nervous system rather than the words spoken. The technology has been validated to correlate with clinical diagnoses at a high accuracy level. It provides real-time, objective assessments to healthcare providers, which could help overcome biases and reveal early signs of the presence of a disease.
Henry explains, "Canary Speech is now about eight years old. Jeff Adams, my business partner and friend, and I created Canary Speech to evaluate voice for a range of different human conditions and diseases. We actually established an approach that was unique in the market. Jeff has a history of innovation in voice and voice analysis. He was the lead that developed the first natural language processing commercial tools. He also led the team that developed Dragon naturally speaking, the most prominent tool for transcription services in healthcare. He also led the team that built the Amazon Echo."
"With that deep experience and 40 years of relationship together and friendship, we created Canary speech. Canary looks at sub-language characters and elements. We look at 15 million different data elements every minute, and we process those for a range of different diseases, progressive neurological diseases, cognitive health, and behavioral health. We're beginning to build models for children's health."
"Everything that we have built has been built in clinical settings with peer review with organizations such as The Harvard Beth Israel, Hackensack Meridian, Intermountain Healthcare, Cala Hospital in Dublin, Ireland, Belfast Hospital, and Alster Hospital in Belfast, and also National Institutes of Health in Japan. So, we use those rigorous environments and those clinical settings to build local biomarker algorithms that can identify."
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